21st EANN 2020, 5 -7 June 2020, Greece

Eye Movement Data Analysis

Olga Georgieva, Nadejda Bocheva, Bilyana Genova, Miroslava Stefanova


  The aim of the present study is to investigate the separation abilities of three statistical parameters for grouping participants in the visual-motor experiment by their age and gender. These parameters represent different characteristics of the decision-making process and were determined by applying the hierar-chical drift diffusion model to the response time and accuracy of the exper-imental data. The objective function cluster analysis was applied to ex-plore distinct data spaces formed by the parameters’ data. The ability for grouping is assessed and interpreted according to the differences in the sub-jects’ capabilities to perform the visuo-motor task. The study compares the conclusions based by drift-diffusion model using Bayesian parameter esti-mation with those based on the cluster analysis in terms of ability to distin-guish the performance of different age groups. The investigation of gender effects are uniquely investigated by cluster analysis technique.  

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